Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Development of Novel Diagnostic Tools for Dry Eye Disease using Infrared Meibography and In Vivo Confocal Microscopy

Dry eye disease (DED) is a multifactorial disease of the ocular surface where tear film instability, hyperosmolarity, neurosensory abnormalities, meibomian gland dysfunction, ocular surface inflammation and damage play a dedicated etiological role. Estimated 5 to 50% of the world population in different demographic locations, age and gender are currently affected by DED. The risk and occurrence of DED increases at a significant rate with age, which makes dry eye a major growing public health issue. DED not only impacts the patient’s quality of vision and life, but also creates a socio-economic burden of millions of euros per year. DED diagnosis and monitoring can be a challenging task in clinical practice due to the multifactorial nature and the poor correlation between signs and symptoms. Key clinical diagnostic tests and techniques for DED diagnosis include tearfilm break up time, tear secretion – Schirmer’s test, ocular surface staining, measurement of osmolarity, conjunctival impression cytology. However, these clinical diagnostic techniques are subjective, selective, require contact, and are unpleasant for the patient’s eye. Currently, new advances in different state-of-the-art imaging modalities provide non-invasive, non- or semi-contact, and objective parameters that enable objective evaluation of DED diagnosis. Among the different and constantly evolving imaging modalities, some techniques are developed to assess morphology and function of meibomian glands, and microanatomy and alteration of the different ocular surface tissues such as corneal nerves, immune cells, microneuromas, and conjunctival blood vessels. These clinical parameters cannot be measured by conventional clinical assessment alone. The combination of these imaging modalities with clinical feedback provides unparalleled quantification information of the dynamic properties and functional parameters of different ocular surface tissues. Moreover, image-based biomarkers provide objective, specific, and non / marginal contact diagnosis, which is faster and less unpleasant to the patient’s eye than the clinical assessment techniques. The aim of this PhD thesis was to introduced deep learning-based novel computational methods to segment and quantify meibomian glands (both upper and lower eyelids), corneal nerves, and dendritic cells. The developed methods used raw images, directly export from the clinical devices without any image pre-processing to generate segmentation masks. Afterward, it provides fully automatic morphometric quantification parameters for more reliable disease diagnosis. Noteworthily, the developed methods provide complete segmentation and quantification information for faster disease characterization. Thus, the developed methods are the first methods (especially for meibomian gland and dendritic cells) to provide complete morphometric analysis. Taken together, we have developed deep learning based automatic system to segment and quantify different ocular surface tissues related to DED namely, meibomian gland, corneal nerves, and dendritic cells to provide reliable and faster disease characterization. The developed system overcomes the current limitations of subjective image analysis and enables precise, accurate, reliable, and reproducible ocular surface tissue analysis. These systems have the potential to make an impact clinically and in the research environment by specifying faster disease diagnosis, facilitating new drug development, and standardizing clinical trials. Moreover, it will allow both researcher and clinicians to analyze meibomian glands, corneal nerves, and dendritic cells more reliably while reducing the time needed to analyze patient images significantly. Finally, the methods developed in this research significantly increase the efficiency of evaluating clinical images, thereby supporting and potentially improving diagnosis and treatment of ocular surface disease

The Biopigment Eumelanin in the Sustainability Challenge: Interfaces With Metal Electrodes, UV-Absorption Enhancement of Plastics and its Biodegradability

L’Organisation des Nations Unies (ONU) définit le développement durable comme la capacité d’une génération de satisfaire ses propres besoins « sans compromettre la possibilité des générations suivantes de satisfaire les leurs ». Le domaine de l’électronique est marqué par la croissance effrénée des déchets d’équipements électriques et électroniques (DEEE) et par l’épuisement des ressources nécessaires à la fabrication des EEE. L’utilisation de matériaux organiques (constitués de carbone) naturels (biosourcés), biodégradables et traités à l’aide de solvants non toxiques, est alors une solution à considérer pour réduire l’empreinte écologique de l’électronique. L’eumélanine, sous-catégorie noire/marron de la mélanine (pigment omniprésent dans la faune et la flore), présente une absorption optique étendue sur les spectres ultraviolet (UV) et visible, une réponse électrique dépendante du niveau d’hydratation, des propriétés de chélation des métaux et de piégeage des radicaux ainsi qu’une structure moléculaire qui comporte des groupements fonctionnels redox. L’eumélanine est donc un matériau prometteur dans l’électronique organique verte. L’électronique organique utilise des matériaux conducteurs ou semiconducteurs à base de carbone, qui présentent une alternance de liaisons simples et doubles carbone-carbone (systèmes conjugués). Ces matériaux, outre leur flexibilité mécanique, peuvent être traités en solution. Les dispositifs à base de matériaux organiques se distinguent, par conséquent, par leur faible énergie intrinsèque (l’énergie consommée pendant leur fabrication), comparés à la majorité des dispositifs à base de matériaux inorganiques pour lesquels le processus de fabrication implique de hautes températures et des très baisses pressions (vide élevé). Les efforts pour rendre le développement plus durable concernent aussi les matériaux organiques isolants (plastiques) pour les emballages et leurs additifs nécessaires pour améliorer certaines propriétés telles que la stabilité thermique et l’absorption des rayons UV. Le coeur de cette thèse est consacré à l’étude de plusieurs propriétés fonctionnelles de l’eumélanine dans le cadre d’une utilisation potentielle dans les technologies liées à l’électronique organique verte ainsi que dans le domaine des additifs plus respectueux de l’environnent pour les plastiques. Le Chapitre 1 présente la mélanine, avec une attention particulière portée à l’eumélanine et ses propriétés.----------Abstract The United Nations define sustainability as the ability to meet one generation’s needs “without compromising the ability of future generations to meet their own needs”. The field of electronics features a dramatic increase of waste electrical and electronic equipment (WEEE) and the depletion of key elements necessary for EEE fabrication. The use of biodegradable organic (carbon-based) materials extracted from natural sources (bio-sourced) and processed with non-toxic solvents represents a valuable option to alleviate the environmental footprint of the electronic sector. Eumelanin, a dark-brown subcategory of melanins (a ubiquitous biopigment in flora and fauna), features broad ultraviolet-visible absorption, hydration-dependent electrical response as well as metal chelation, radical scavenging and redox activity. Eumelanin is a promising candidate in the field of green (sustainable) organic electronics. Organic (plastic) electronics is based on carbon-based conducting and semiconducting polymers and small molecules that feature conjugation (alternance of single and double carbon-carbon bonds) in their molecular structure. In addition of being mechanically flexible, devices based on organic electronic materials can be solution-processable and thus stand for their lower embodied energy (i.e. “energy spent in the production phase and stored in the inner constituents”) with respect to most inorganic ones, which are processed at high-temperature and under high-vacuum conditions. Sustainability is an issue also in the field of (non-conducting) plastics for packaging, where it concerns not only the packaging polymers but also the additives needed to enhance certain properties, such as thermal stability or ultraviolet (UV) radiation absorption. The core of this PhD thesis is devoted to the study of a number of functional properties of eumelanin in view of its use in sustainable organic electronic technologies as well as a greener additive for plastic packaging. Chapter 1 gives an overview on melanins, with a focus on the subcategory eumelanin and its properties. Chapter 2 provides a review of the state of the art of the potential applications of eumelanin demonstrated in the literature. Chapter 3 details the targets of the research: the investigation of eumelanin-metal interfaces under bias, the study of eumelanin as an additive for plastics and the assessment of eumelanin’s biodegradability. Chapter 4 briefly explains the characterization techniques used

Solidification behavior of high nitrogen stainless steels and establishment of a one-dimensional heat transfer framework

Duplex stainless steel (DSS) has excellent corrosion resistance and mechanical properties due to its dual-phase structure. The solidification process is the key to determining the structure of materials, and an in-depth investigation of solidification can help us better understand the properties of materials. The melting and solidification processes of S32101 DSS were investigated using high temperature confocal microscopy (HTCM)